Dergiler / Diagnostic and Interventional Radiology / 2016 / Cilt: 22 - Sayı: 6

Pulmonary adenocarcinomas presenting as ground-glass opacities on multidetector CT: three-dimensional computer-assisted analysis of growth pattern and doubling time

Sayfa
525–533
DOI
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Abstract

PURPOSE We aimed to evaluate the growth pattern and doubling time (DT) of pulmonary adenocarci-nomas exhibiting ground-glass opacities (GGOs) on multidetector computed tomography (CT).METHODSThe growth pattern and DT of 22 pulmonary adenocarcinomas exhibiting GGOs were retrospec-tively analyzed using three-dimensional semiautomatic software. Analysis of each lesion was based on calculations of volume and mass changes and their respective DTs throughout CT fol-low-up. Three-dimensional segmentation was performed by a single radiologist on each CT scan. The same observer and another radiologist independently repeated the segmentation at the baseline and the last CT scan to determine the variability of the measurements. The relationships among DTs, histopathology, and initial CT features of the lesions were also analyzed.RESULTSPulmonary adenocarcinomas presenting as GGOs exhibited different growth patterns: some le-sions grew rapidly and some grew slowly, whereas others alternated between periods of growth, stability, or shrinkage. A significant increase in volume and mass that exceeded the coefficient of repeatability of interobserver variability was observed in 72.7% and 84.2% of GGOs, respectively. The volume-DTs and mass-DTs were heterogeneous throughout the follow-up CT scan (range, -4293 to 21928 and -3113 to 17020 days, respectively), and their intra- and interobserver variabil-ities were moderately high. The volume-DTs and mass-DTs were not correlated with the initial CT features of GGOs; however, they were significantly shorter in invasive adenocarcinomas (P = 0.002 and P = 0.001, respectively).CONCLUSIONPulmonary adenocarcinomas exhibiting GGOs show heterogeneous growth patterns with a trend toward a progressive increase in size. DTs may be useful for predicting tumor aggressiveness